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Questions tagged [sensitivity-analysis]

Auxiliary methods intended to check if the outcome of an analysis strongly depends on the model assumptions, preprocessing steps, presence of outliers, etc.

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Sensitivity Analysis with categorical predictive variables in R

I am doing a project where I have to predict the Sales Units in fashion and intend to run a Random Forest, Neural Networks and Support Vector Machine models. However, my predictive variables are all ...
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33 views

Which approach should be used to compare two different measurement techniques of same samples?

I have individually measured failure forces of 8 materials and those recorded with A method and B method in same time: 8 results in each method, A=8 and B=8. The range of data of both measurement ...
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Understanding Conditional Variance Decomposition for Sensitivity Analysis (Sobol Indices)

I am trying to understand both terms of a formula that describe the variance of a model output, Y, in terms of its conditional variance, as below: $E_{X_i}\left(V_{X_{--i}}\left(Y\middle| X_i\right)\...
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What is the difference between sensitivity analysis and correlation analysis?

How do you compare them with each other in the statistical context? I have a set of inputs and outputs for which I build a random forest model. Can I use the model to perform sensitivity analysis ...
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Sensitivity of regression parameters to noise

How sensitive are the parameters obtained from OLS, logistic or other regression methods to noise ? By noise, I mean minor changes. For e.g. adding a small noise $-1<\Delta<1$ to $\beta_1$ in $...
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Analyse sensitivity of hyper-parameters of Machine Learning Models

I want to analyse how sensitive my non neural net machine learning models are to the choice of the different parameters. I am currently using grid search to tune the models. Is there any method that I ...
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67 views

Global sensitivity Morris method - choice of delta and normalisation of the elementary effects

I have few questions regarding the Morris method (as decribed e.g. in Campolongo, Cariboni, Saltelli, Environmental Modelling & Software 22, 2007 or Wenthworth et al. J. Uncertainty Quantification ...
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26 views

Different result in sensitivity analysis

the result of the sensitivity analysis when changing the below equation from using market value to book value as the measurement of leverage, Leverage = β0 + β1 PROF + β2 SIZE + β3 TANG + β4GROWTH +...
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comparing sensitivities

We want to compare two sampling methods. All patients will go through a DNA test for diagnosis(positive or negative). Then samples are taken to identify the determine the type of bacteria and ...
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Sensitivity index from Spearman's Rank-Order Correlation Coefficient

I calculated the Spearman's Rank-Order Correlation Coefficients for all free variables (over 200) in a model. I have about 5000 samples, and get comfortably small p values. I was wondering whether I ...
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82 views

Latin hypercube sampling with categorical variables

I would like to run sensitivity analyses on my agent-based model. My model has 20 parameters that I need to vary. I generated 8 artificial landscapes that vary in resource aggregation (r) and my model ...
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Calculate the contribution of features within a sentiment analyses

I did a sentiment analysis using the sentiwordnet lexicon. The sentiment analyses was done on Tweets, which were annotated as positive, negative or neutral. Now I want to know which features in the ...
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Fitting multiple polynomial regression

I hope someone could advise to interpret and report outputs of the multiple polynomial regression fit. I am trying to do a simple sensitivity analysis of an empirical threshold-based ecological model ...
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48 views

Sensitivity analysis of transition probabilities in a Markov chain

Does anyone know of a method of sensitivity analysis for investigating the effect of perturbing transition probabilities $p_{ij}$ from a Markov transition matrix? I have a series of n=400 sequences ...
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Sensitivity and specificity on cases rather than individual days

I have data collected from sensors to detect disease in several individuals. Each individual has a known disease status (labelled Actual in the table below) for ...
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30 views

Evaluating Impact of Unobserved Confounders - Is the E-Value applicable for Non-Significant Group Differences?

I have conducted an analysis of treatment effects based on observational data (via statistical matching). As suggested by VanderWeele and Ding (2017), I want to evaluate the sensitivity of my analysis ...
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32 views

Is there an accepted way to interpret d' (d-prime) for evidence of detection

I have run a learning experiment, with a yes-no familiarity test at the end, and computed d' across various conditions. Is there some rule of thumb (perhaps dependent on sample size) as to how d' ...
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25 views

What is the correct parameter range to choose when conducting a sensitivity analysis?

When conducting a (variance-based) sensitivity analysis, should I set the range of a specific parameter to its maximum allowable range, or restrict it to something more appropriate for my specific ...
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When is it justifiable to ignore explanatory variable endogeneity in a regression model?

I have three related questions: Is there a way to conduct a back of the envelop calculation that informs the reader on the degree of endogeneity we should have to bias the OLS estimates in a ...
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Sensitivity study: measuring the effects of free parameters on performance measures of simulation

I am running a series of computer simulations in which I am outputting several performance measures. I want to know how much of the variability of these measures is due to the free parameters of the ...
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86 views

Causal Mediation Analysis Sensitivity Analysis

As part of a research project we have to perform causal mediation analysis(CMA) on R. Since mediation package is kind of limited for our research purposes, we ...
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84 views

Sensitivity Measures for GEE Model

Is there any method (e.g. like Cooks D) implemented in R to identify leverage points for GEE Models? I used geepack to fit my models and would like to do a sensitivity analysis now. However, I don't ...
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146 views

Unstable feature importance and optimized mtry values in Random Forest

I am working with a dataset of 17 predictors and 1000 observations. I am trying to find the most important variables, for which I am using the permutation-based OOB-MSE. My problem is that each time ...
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136 views

Sobol method vs OAT approach

I have used one at a time (OAT) approach in my model for sensitivity analysis. Which gives me elementry effects and variances for the input parameters, helping me to eliminate the less influencial ...
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645 views

How to analyses sensitivity for understanding which variables are the most effect on the predictive model

I have a dataset with 150 observations. The dataset has 9 input parameters and 1 output parameter. I have built a predictive model (Random Forest) using the dataset. And now, I want to know that which ...
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How to carry out a 5 input 5 output sensitivity analysis?

I have a vehicle (truck) model. There are five inputs, which are: Turn Radius Longitudinal slope (going up or down= Cross slope of the road Road friction Cargo weight By varying each of these inputs ...
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226 views

Difference between Sensitivity analysis and Design of Experiments

Reading on wikipedia about the methods for sensitivity analysis: different methods are stated. At the end of the wikipedia page, a section called Related Concepts speaks about Design of experiments (...
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237 views

Sobol Sensitivity Analysis

I want to use Sobol SA with Sobol sampling to find the most influential parameters on the energy consumption of a pilot building. I have 40 input variables (building characteristics) that some have ...
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79 views

Unexpected Negative Partial Derivatives for Input Features to Neural Network

Using a relatively standard MLP neural network, I model the total duration of an activity based on many counts of sub-activities, where the relationships between the sub-activities and duration may be ...
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690 views

Understanding Sobol in R Package Sensitivity

Sobol method quantifies the contributions of input variance to output variance. For example, given a model with two inputs and one output, one might find that 70% of the output variance is caused by ...
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107 views

one way sensitivity analysis with categorical variables

I am studying the impact of different factors on the expected price change for drugs. I have a regression model that looks like the following: Y=a+B1x1+B2x2... I would like to conduct some one-way ...
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145 views

Prior sensitivity analysis: The case of a Beta prior

I had a question regarding how to best perform "sensitivity analysis" on a Beta prior used for a estimating a proportion from a binomially distributed data problem (i.e., beta-binomial problem). I ...
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What is the correct method for comparing sensitivity and specifity of different tests?

What is the correct method of comparing efficiency of different test for one sample of individuals? Are ROC and AUC enough? Comparing of sensitivity and specifity values of the tests with McNemar ...
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28 views

How to evaluate sensitivity and specifity of different tests

I am comparing two test using different cut-off values with golden standart test . How is it to be reported. Is it sufficent to report sensitivity, specivity, PPV and NPV with 95 CI or should I ...
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How to choose a ML model when the goal is both reasonable prediction AND inference?

I'm relatively new to machine learning. I have come across the "ML is for prediction not inference” statement but this did not really sink in until my current project, a marketing mix modelling ...
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Linear Regression: How to favour less “sensitive” parameters?

I have a simple regression model (y = param1*x1 + param2*x2). When I fit the model to my data, I find two good solutions: Solution A, params=(2,7), is best on the training set with RMSE=2.5 BUT! ...
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391 views

Categorical data in sensitivity analyses

I have a model that will evaluate the carbon footprint of a product (i.e. tally the greenhouse gas emissions that were generated in each of the activities required to make, use and dispose of the ...
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1answer
35 views

Uncertainty and sensitivity analysis on modelling problems [closed]

I am starting to write the literature review for a project and my supervisor wants me to do an Uncertainty analysis and sensitivity analysis for a Modelica model he has. I am new to both concepts, do ...
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How many sobol sequences should I generate for sensitivity analysis?

I have a benchmark application that has 10 variables of different ranges. The application has one output a value measuring the performance of the application. I want to determine which of the ...
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1answer
83 views

Implementation of the weighted sum model without knowing the weights

I am looking to combine n metrics to obtain 1 single unified metric. For example, let's say I have 2 metrics n1 and n2 for k elements. I am particularly interested in the one or two elements that have ...
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437 views

sensitivity analysis when only input and output values are available in R

I was asked to evaluate how the output changes in response to input variables. For this I have randomly create sensible value of input variables. These are then imported into a software which yields ...
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67 views

Sensitivity analysis of election poll correlation

I am interested in why the 2016 presidential election polls did a poor job in forecasting the result. One hypothesis I heard is that many of the polls conducted before the election were correlated, ...
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4k views

Sensitivity and Specificity calculations

My confusion matrix is as shown below ...
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1answer
452 views

Interpretation of second-order sensitivity indices from 'sensitivity' package in R?

I am trying to understand the importance of input factors in constructing a composite indicator. I am using global sensitivity analyses in R's 'sensitivity' package. Using 'sobolSalt', there is a ...
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5k views

Sensitivity Analysis in Deep Neural Networks

Following a question already answered (Extracting weight importance from One-Layer feed-forward network) I am looking for inference about relevance of inputs in neural networks. Considering a deep ...
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Stacking sensitivity analysis

I conducted stacking of three algorithms (NN, J48 and BN) with logistic regression as the meta-classifier. I am interested in doing a sensitivity analysis so I am able to rank the predictors and ...
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What do people mean by “sensitivity analysis”

I have seen and heard people use "sensitivity analysis" to refer to both: How different values (e.g., just males or the whole cohort) of an independent variable affects the model, and How the ...
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Is medsens() also appropriate for moderated mediation?

medsens() is a fantastic R-method for testing sensitivity of mediation models estimated by mediate() method (mediation package by Tingley et al; Version 4.4.5). However, I'm wondering whether medsens()...
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588 views

global sensitivity analysis input and output matrix

I am performing nonlinear analysis in ABAQUS software, with 5 input variables. For each realization of the input vector, I run the code and I get a scalar response value. I am using the Monte Carlo ...
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How to set up a proper prior sensitivity analysis?

Working with Bayesian econometrics I am regularly faced to the (valid) question: How does your prior choice affect the results? Given my parameter space is of rather low-dimension I may come up ...